{"id":"W2055955832","doi":"10.1109/icpads.2011.24","title":"An Efficient Video Adaptation Scheme for SVC Transport over LTE Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Computer network; Scalable Video Coding; 3rd Generation Partnership Project 2; Unicast; Video quality; Multicast; Network packet; Real-time computing; Packet loss; Throughput; Cellular network; Jitter; Wireless; Scalability; Telecommunications; Telecommunications link","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004402249,0.000301048,0.0003017253,0.0003494449,0.0003472957,0.0003013829,0.000438589,0.0003048431,0.0004942189],"category_scores_gemma":[0.0008057891,0.00009342097,0.0001692603,0.0002758471,0.0002268945,0.0003457858,0.0002741273,0.000410696,0.0001528577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000553526,"about_ca_system_score_gemma":0.0003397104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003097869,"about_ca_topic_score_gemma":0.003111149,"domain_scores_codex":[0.9997659,0.00004417005,0.0000155365,0.00002759595,0.0001142986,0.0000325326],"domain_scores_gemma":[0.9996691,0.00007169593,0.00003707021,0.00005561003,0.0001479909,0.00001856756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007757428,0.0002377792,0.002024893,0.00009581551,0.00007730785,0.0004790406,0.0001820917,0.1352988,0.5073717,0.008675922,0.002842202,0.3419386],"study_design_scores_gemma":[0.00002231993,0.0002460548,0.001175613,0.000007598407,0.00002815877,0.0002770862,0.00002876231,0.9353002,0.060117,0.000756524,0.002013481,0.00002725429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2611104,0.0005797574,0.733072,0.0001767102,0.00012432,0.0002189528,0.00009705958,0.001403194,0.003217551],"genre_scores_gemma":[0.9335977,0.0001764649,0.06439142,0.00005566074,0.0000349582,0.00005201836,0.0001361188,0.00002563283,0.00153004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003097869,"threshold_uncertainty_score":0.006159663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05020100519921702,"score_gpt":0.2554395719199862,"score_spread":0.2052385667207691,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}